Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add ThomasMoreAI/legal-skills-open --skill prompt-pack-social-media-knowledge-content-prompt-sboghossiangit clone --depth 1 https://github.com/ThomasMoreAI/legal-skills-openWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/thomasmoreai/legal-skills-open/prompt-pack-social-media-knowledge-content-prompt-sboghossian)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/prompt-pack-social-media-knowledge-content-prompt-sboghossian"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/prompt-pack-social-media-knowledge-content-prompt-sboghossian/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/prompt-pack-social-media-knowledge-content-prompt-sboghossian"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/prompt-pack-social-media-knowledge-content-prompt-sboghossian.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00104 | $0.02084 |
| Opus 5.5 | $0.00042 | $0.00834 |
| Sonnet 5.5 | $0.00021 | $0.00417 |
| Haiku 4.5 | $0.00010 | $0.00208 |
Grade A, and why
prompt-pack-social-media-knowledge-content-prompt-sboghossian scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 26d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Social Media / Knowledge Content Prompt
When to use this
Use this skill when a lawyer, law firm, or legal content team needs to:
- Translate a new law, regulatory change, or legal concept into an accessible LinkedIn or X/Twitter thread for clients, business professionals, or the public.
- Create thought-leadership content that demonstrates expertise without providing individualized legal advice.
- Explain a jurisdiction-specific legal issue (UAE corporate tax, Saudi labour reform, DIFC employment law update) in a format that clients and prospects will actually read.
- Prepare content for a firm newsletter, website, or knowledge hub in a social-media-friendly format.
Key constraint: Social media legal content must be educational, not advisory. The content explains a legal framework or concept; it does not constitute legal advice for any specific situation. A disclaimer must be included.
Required inputs
| Input | Why it matters | Default if omitted |
|---|---|---|
| Topic or legal issue | The core of the post | Ask; the more specific the better ("UAE Corporate Tax impact on free zone companies" beats "UAE tax") |
| Target audience | General public / business owners / in-house lawyers / CFOs | Ask; determines language complexity and which aspects to emphasize |
| Platform | LinkedIn (long-form, professional) vs. X/Twitter (short threads) vs. both | Default: LinkedIn primary, X/Twitter thread as secondary |
| Jurisdiction focus | Ensures accuracy for local rules | Ask; default to UAE if MENA context |
| Firm tone / voice | Authoritative but accessible; some firms prefer formal; others conversational | Ask; default: professional and approachable |
Optional inputs
- Recent trigger event — a new law published in the Official Gazette, a regulatory announcement, a court decision; timely content performs better.
- Case study or example — concrete examples dramatically improve engagement; if a (sanitized) client scenario is available, use it.
- Word count / post length target — LinkedIn allows up to 3,000 characters; a LinkedIn article allows more; specify.
- Images or infographic brief — if a visual (flowchart, comparison table) is to accompany the text, describe the visual concept.
- Call to action — "contact us for a consultation," "download our guide," "subscribe to our newsletter," etc.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 26d ago First seen · 138 lines · 104 tokens per session scan A 2f21d901295d
prompt-pack-social-media-knowledge-content-prompt-sboghossian is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (95 stars, last pushed 15d ago), licensed Apache-2.0. It adds 104 tokens to every session and 2,084 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-10-02.
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